Metabolite profiling is an emerging science that is used in determining gene function, effects of genetic engineering on an organism, substantive equivalence, drug mechanisms of action, adverse drug reaction monitoring and the biochemical basis of diseases. Non-targeted metabolic profiling using FT-ICR-MS identifies a large number of metabolites from complex biological extracts. The final output from such analyses is the masses and intensities of observed metabolites. The masses can be used to determine the molecular formulas, and thus the identity of the metabolites present in the sample, whereas the intensity is used to determine the amount of the metabolite present in the sample. By comparing the metabolite profiles of different biological samples, metabolite changes can be observed. These biochemical changes can then be used to understand the effect of the experimental event.
Although multiple visualization tools have been developed to display mass spectral and chromatographic data as well as databases to store, organize, and search this type of data, these tools work only for targeted analyses of known molecules. Currently, there is no effective way to display or organize information from multiple non-targeted sample analyses such that a user can quickly identify changes in metabolite profiles.
The ability to view and interpret large amounts of metabolite data is a rate-limiting step in the study of biological systems using non-targeted metabolomic methods. The creation of a process that would allow users to quickly interpret and report their findings would dramatically reduce the time and thus the cost of functional genomics utilizing non-targeted metabolomics.
There is a need in the art for novel methods of displaying data obtained by analytical instruments. Further, there is a need in the art for novel methods of displaying or visualizing data from large numbers of non-targeted samples. Also, there is a need in the art for methods and data structures to organize and display in a 2-D array format, non-targeted metabolomic data arising from FT-ICR-MS. There is also a need to link the displayed data to additional databases to characterize or analyse further the displayed data.
It is an object of the present invention to overcome disadvantages of the prior art.
The above object is met by a combination of the features of the main claims. The sub claims disclose further advantageous embodiments of the invention.